A novel algorithm for finding reducts with fuzzy rough sets

Degang Chen, Lei Zhang, Suyun Zhao, Qinghua Hu, Pengfei Zhu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

101 Citations (Scopus)

Abstract

Attribute reduction is one of the most meaningful research topics in the existing fuzzy rough sets, and the approach of discernibility matrix is the mathematical foundation of computing reducts. When computing reducts with discernibility matrix, we find that only the minimal elements in a discernibility matrix are sufficient and necessary. This fact motivates our idea in this paper to develop a novel algorithm to find reducts that are based on the minimal elements in the discernibility matrix. Relative discernibility relations of conditional attributes are defined and minimal elements in the fuzzy discernibility matrix are characterized by the relative discernibility relations. Then, the algorithms to compute minimal elements and reducts are developed in the framework of fuzzy rough sets. Experimental comparison shows that the proposed algorithms are effective.
Original languageEnglish
Article number6095617
Pages (from-to)385-389
Number of pages5
JournalIEEE Transactions on Fuzzy Systems
Volume20
Issue number2
DOIs
Publication statusPublished - 1 Apr 2012

Keywords

  • Attribute reduction
  • discernibility matrix
  • fuzzy rough set
  • minimal element

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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